Prediction of novel drug target Involved in psychosis in Alzheimer ...

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Prediction of novel drug target Involved in psychosis in Alzheimer Disease: A Computational Network study Mrinal Mirsra1

Abstract:

Alzheimer (AD) disease is the most frequent form of dementia. Several structural and functional genomic factors are strongly associated with AD candidate genes, including age of onset, cognitive decline and amyloid depositions. Serotonin (5Febin Prabhu Dass. J1* TH) receptors play an important role in psychosis in AD with cognitive impairment. This study is based on insilco identification and prioritization of the differentially 1 Bioinformatics Division, School of expressed genes of the genetic network involved in AD. Fourteen 5-HT candidate Biosciences and Technology, VIT genes interaction network associated with AD was generated using agilent University, Vellore. Tamil Nadu literature search cytoscape plugin. The organic layout shows cross-interaction State, India. 632014. between the genes set. On merging the genetic network with gene expression 2 Enterprise and Cloud Computing, profile data, notable changes in interaction patterns were observed. These School of Information Technology changes revealed 5-HTR2A, 5-HTR2C and 5-HTR4 as important genes in AD. Further & Engineering, VIT University, refinement with Enrichment Map indicated 5-HTR2C as novel candidate gene that Vellore. Tamil Nadu State, India. showed high functional significance in correlation to Alzheimer's disease. Our result 632014. will be a crucial factor for better understanding of the genetic pathways involved in causing psychosis in AD and will form a future landmark in developing target Corresponding Authors: based drug therapies against this disease. Febin Prabhu Dass. J Associate Professor, Bioinformatics Division, eywords: Within family interaction;co-expression;major target, computational School of Biosciences and network analysis of alzheimers Technology, VIT University, Vellore, Tamil Nadu, India. 632014. Email: [email protected]

Kiruba Thangam.

R2

Introduction:

receptor (5HT) are associated with hallucinatory

Alzheimer disease (AD) is a neurodegenerative

demented cohorts. 7 major receptors classes (5-

disorder propagating dementia .This is clinically

HT1-7)

characterized

cognitive

comprising a total of 14 distinct mammalian 5-HT

severe

receptor subtypes. Recent genetic studies in AD

neuropsychiatric disturbances. Deregulation of

showed co-existence of several polymorphisms of

serotonergic neurotransmitter system is credited to

the

cause AD on wide scale. The impaired neuronal

neuropsychotic symptoms. Gene polymorphism in

signalling cascades serotonergic deregulation

5-HT receptor resulting in the change of the gene

affecting the proteolysis of the amyloid precursor

expression

protein (APP) and stimulate amyloid formation in

associated with visual and auditory hallucinations

the brain.

or psychosis in patients with AD. A 44–base pair

Although the origin of psychotic symptoms in

(bp) insertion (the long or l form) of the 5-HTT

Alzheimer’s

multi-factorial,

promoter region (5-HTTPR) was reported to be

alterations in serotonergic neurotransmission are

associated with psychosis and aggression in AD. A

often implicated. Polymorphisms of the serotonin

variable

impairment

symptoms and delusions in demented and non-

by

progressive

associated

disease

(AD)

with

is

mediates

serotonin

5-HT

metabolic

neurotransmitter

level

number

has

been

tandem

pathway

genes

reported

repeat

and

to

be

(VNTR)

Covered in Scopus & Embase, Elsevier Int. J. Drug Dev. & Res., July - September 2014, 6 (3): 147-152 © 2014 Febin Prabhu Dass. J et al, publisher and licensee IYPF. This is an Open Access article which permits unrestricted noncommercial use, provided the original work is properly cited.

Full Length Original Research Paper

Page 147

K

polymorphism in intron 2 of the 5-HTT gene was

Materials and Methods:

unipolar or bipolar depression in AD. The change

Dataset Collection

in the specific genetic expression pattern also

Serotoninergic receptors previously reported to

results in cascading the change in expression

play important role in Brain ageing and based on

pattern to the other associated genes of the

extensive literature searching, we selected 14

genetic network pathway directly or indirectly. This

candidate

change can vary the resulting gene products of

serotoninergic receptors. Collections of expression

diverse genes in the network greatly affecting the

profiles for the 98 important genes involved in the

other different pathways.

genetic network were done from NCBI Geo profile

In our study, Multiple 5-hydroxytryptamine (5-HT)

database.

genes along with other genes of the genetic

Development of genetic network using Cytoscape

network were observed but only few of these 5-HT

Cytoscape

genes when differentially expressed are reported

apprehending networks using Zoomable User

to cause Alzheimer disease (Fig 1). We used

Interface. The directing through this interface is

Cytoscape

for generating and visualising

based on two processes namely zooming and

genetic interaction network. Different Cytoscape

panning. Zooming changes the dimensions of the

plugins were used to assist the generation and

view based on the user need. Panning enables

analysis of the network with extreme accuracy.

the users to direct the focus of a screen to

Obtained

Genetic

different location of a view. Agilent Literature

candidate

genes

[4]

network were

then

comprising

the

prioritize

and

search

[5]

genes

is

which

used

for

code

these

directing

and

was used to scan the genetic network

analyzed by merging with the genetic expression

through published literatures.

of the differentially expressed genes in AD which

within cytoscape and is a meta search tool that

on

map

have a ability of integrating the information and

generated on the basis of differentially expressed

knowledge extraction to generate the genetic

genes regrouping and categorising the genes

network from literatures using Pubmed, OMIM and

corresponding to their expression giving the most

USPTO

refined results.

candidate genes. For generating the genetic

further

analysis

with

enrichment

network

search

it

engines

uses

User

It work parallely

when

fed

with

context-based

the

symbol

normalization. Genetic expression profile data of all the genes of the genetic network from NCBI geoprofile database were extracted and saved as a file in pvals format. The file was merged with normal genetic network. Enrichment map[7] (Fig 2) for

the

differentially

expressed

genes

were

generated for further analysis and refinement of the result which clusters the genes according to correlation with each other giving three clusters of Fig 1: Network before merging genetic map

gene differentiated on the basis of the preference


Page 148

Sudha. S et al; The influence of calreticulin on oxidative stress in MCF-7 cells

also reported to associated with susceptibility to

of expression profile data of the differentially expressed genes.

Result and Discussion: Cytoscape is used for generating and

Page 149

visualising the genetic network involved in causing Fig 2: Enrichment Map for the expressed genes

Alzheimer’s disease. We tested the functional

Visualisation of the genetic network

significance

Vizmapper

[6]

was used for assisting the

of

hydroxytryptamine

differentially (5HT)

expressed

genes

in

5-

causing

Visualisation of the genetic network merged with

Alzheimer’s disease. We selected 14 candidate

genetic expression profile data by setting the

genes (5-HT1A, 5-HTR1B, 5-HTR1D, 5-HTR1E, 5HTR1F,

parameters for size and color of the nodes and

5-HTR2A, 5-HTR2B, 5HTR2C, 5-HT4A, 5-HTR4B, 5-

edges according to expression profile data of the

HT5A, 5-HTR5B, 5-HT6 and 5-HT7) for building the

genes (Fig 3). On visualising and analysing the

genetic network involved in causing Alzheimer’s

genetic network merged with expression profile

disease. Fig 1. shows the normal genetic network

data elucidates most potent genes that could be

before merging with genetic expression profile

very crucial in causing Alzheimer disease.

data whose edges and nodes colours and sizes parameters are set according to outdegree of each gene in the network. This network shows HTR1A, HTR2A, HTR6, BIN1, CR1 and APOE having maximum outdegrees distribution [Fig 4] and average clustering coefficient (Fig 5).



Fig 3: Network after merging genetic map

CLU[8,

9],

IN1[9], PDYN[10], ABCA8[11], HSP90AA1[12],

GRIA2[13],

APP[14],

CAMKV[15],LRP2[16],

PRDM2[17],MAP1B[18] ,BMP7[19] and MTM1[20] are previously reported to play significant role in causing Alzheimer disease. The result obtained in this study reports HTR2C as a significant candidate

observation

will

development Fig 4: Outdegree distribution in the network

of

provide new

a

landmark

drug

targets

for

against

Alzheimer's.

References: 1)

Qiu C1, Kivipelto M, von Strauss E. Epidemiology of Alzheimer's disease: occurrence, determinants, and strategies

toward

intervention.

Dialogues

Clin

Neurosci 2009: 11(2); 111-128. 2)

Meneses A. Physiological, Pathophysiological and Therapeutic Roles of 5-HT Systems in Learning and Memory. Reviews in the Neurosciences 1998: 9; 275289.

Fig 5: Average clustering coefficient distribution in the network

3)

E.

A

neuroimaging

review of

of

the

serotoninergic

literature

on

function

in

Alzheimer's disease and related disorders. J Neural

These results suggest a significant role of these genes in regulating the corresponding genetic

Salmon

Transm. 2007 :114(9);1179-1185. 4)

network. Further we merged the expression datas

Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T.

for the genes in network to examine the variations

Cytoscape: A Software Environment for Integrated

induced due to changes in the expression values

Models

of corresponding genes. Genetic network merged

Genome Res 2003:13; 2498-2504.

with genetic expressions reveals the importance of

5-HTR2A,5-HTR2C

and

5-HTR4

in

5)

cut-off

value

=

0.375).

Enrichment

Interaction

Networks.

A.

An

architecture

extraction

and

for

biological

representation.

Bioinformatics 2005: 21(4); 430-438.

the observation obtained through Enrichment map (with Jacard + overlap coefficient combined

Adler

information

Alzheimer disease which was further supported by

Biomolecular

Vailaya A, Bluvas P, Kincaid R, Kuchinsky A, Creech M,

causing

of

6)

Michael

E.

Smoot,

Keiichiro

Ono,

Johannes

Ruscheinski, Peng-Liang Wang and Trey Ideker.

map

Cytoscape 2.8: new features for data integration

categorized all the differentially expressed genes

and network visualization. Bioinformatics 2011: 27

in Alzheimer disease on the basis of correlation of

(3); 431-432.

the genetic expressions. Among all correlated genes in the Enrichment Map HTR2A[3], PICALM[8, 9],

7)

Merico D, Isserlin R, Stueker O, Emili A, Bader GD. Enrichment map: a network-based method for


Page 150


gene for Alzheimer disease. This methodological

gene-set

8)

enrichment

visualization

and

interpretation. PLoS One 2010: 5(11); e13984.

Novials A. Impairment of the ubiquitin-proteasome

Harold D, Abraham R, Hollingworth P, Sims R, Gerrish

pathway is a downstream endoplasmic reticulum

A, Hamshere ML, Pahwa JS, Moskvina V, Dowzell K,

stress response induced by extracellular human islet

Williams A, Jones N, Thomas C, Stretton A, Morgan

amyloid polypeptide and contributes to pancreatic

AR, Lovestone S, Powell J, Proitsi P, Lupton MK,

beta-cell apoptosis. Diabetes 2007: 56(9); 2284-

Brayne C, Rubinsztein DC, Gill M, Lawlor B, Lynch A,

2294. 13) Zherebtsova AL, Shadrina MI, Semenova EV, Levitskiĭ

McGuinness B, Todd S, Holmes C, Mann D, Smith

GN, Alekhin AV, Slominskiĭ PA, Skvortsova VI,

AD, Love S, Kehoe PG, Hardy J, Mead S, Fox N,

Limborskaia SA. Analysis of the possible involvement

Rossor M, Collinge J, Maier W, Jessen F, Schürmann

of the glutamate transporter gene EAAT2 and the

B, van den Bussche H, Heuser I, Kornhuber J,

glutamate receptor genes GRIA1 and GRIA2 in

Wiltfang J, Dichgans M, Frölich L, Hampel H, Hüll M,

pathogenesis of motor neuron disease in the

Rujescu D, Goate AM, Kauwe JS, Cruchaga C,

Russian population. Genetika 2006: 42(1);104-109.

Nowotny P, Morris JC, Mayo K, Sleegers K, Bettens K,

14) Sabo SL, Ikin AF, Buxbaum JD, Greengard P. The

Engelborghs S, De Deyn PP, Van Broeckhoven C,

amyloid precursor protein and its regulatory protein,

Livingston G, Bass NJ, Gurling H, McQuillin A,

FE65, in growth cones and synapses in vitro and in

Gwilliam R, Deloukas P, Al-Chalabi A, Shaw CE,

vivo. J Neurosci 2003: 23(13); 5407-5415.

Page 151

Tsolaki M, Singleton AB, Guerreiro R, Mühleisen TW,

15) Ly PT, Song W. Loss of activated CaMKII at the

Nöthen MM, Moebus S, Jöckel KH, Klopp N,

synapse underlies Alzheimer's disease memory loss.

Wichmann

J Neurochem 2011: 119(4); 673-675.

HE, Carrasquillo MM, Pankratz

VS,

16) Deane R, Sagare A, Zlokovic BV. The role of the cell

study

surface LRP and soluble LRP in blood-brain barrier

identifies variants at CLU and PICALM associated

Abeta clearance in Alzheimer's disease. Curr Pharm

with Alzheimer's disease. Nat Genet 2009: 41(10);

Des 2008:14(16); 1601-1605.

Williams

J.

Genome-wide

association

17) Rocca WA, Shuster LT, Grossardt BR, Maraganore

1088-1093. Hu X, Pickering E, Liu YC, Hall S, Fournier H, Katz E,

DM, Gostout BS, Geda YE, Melton LJ 3rd. Long-term

Dechairo B, John S, Van Eerdewegh P, Soares H.

effects of bilateral oophorectomy on brain aging:

Alzheimer's Disease Neuroimaging Initiative. Meta-

unanswered questions from the Mayo Clinic Cohort

analysis

for

study

Study of Oophorectomy and Aging. Womens

identifies

multiple

locus

Health (Lond Engl) 2009: 5(1); 39-48.

genome-wide variants

association at

the

BIN1

associated with late-onset Alzheimer's disease. PLoS

Yamamoto T, Kosaka K, Nagai Y, Sawada T, Heese

One 2011: 6(2); e16616. 10) Courtney

C.

Babbitt,Jesse

Haygood,Jennifer

M.

18) Yokota T, Mishra M, Akatsu H, Tani Y, Miyauchi T,

S.

Silverman,Ralph

Reininga,Matthew

V.

Rockman, Gregory A. Wray. Multiple Functional Variants in cis Modulate PDYN Expression. Mol Biol Evol 2010: 27 (2); 465-479. 11) Kim WS, Guillemin GJ, Glaros EN, Lim CK, Garner B.

K. Brain site-specific gene expression analysis in Alzheimer's disease patients. Eur J Clin Invest 2006: 36(11); 820-830. 19) Heredia L, Helguera P, Olmos SD, Kedikian G, Solá Vigo F, LaFerla F, Staufenbiel M, Olmos JD, Busciglio J, Cáceres A, Lorenzo A. Phosphorylation of Actin-

Quantitation of ATP-binding cassette subfamily-A

Depolymerizing

Factor/Cofilin

transporter gene expression in primary human brain

Mediates

cells. Neuroreport 2006:17(9); 891-896.

Potential Mechanism of Neuronal Dystrophy in

Amyloid

-Induced

by

LIM-Kinase

Degeneration:

A



Morgan K, Brown KS, Passmore PA, Craig D,

Younkin SG, Holmans PA, O'Donovan M, Owen MJ,

9)

12) Casas S, Gomis R, Gribble FM, Altirriba J, Knuutila S,

Alzheimer's Disease. J. Neurosci 2006: 26(24); 65336542. 20) Johnson F, Giulivi C. Superoxide dismutases and their impact upon human health. Mol Aspects Med. 2005:26(4-5); 340-352. Article History: ------------------------

Date of Acceptance: 29-09-2013 Conflict of Interest: NIL Source of Support: NONE

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Date of Submission: 16-09-2013
